Netflix! What started in 1997 as a DVD rental service has since exploded into one of the largest entertainment and media companies.
Given the large number of movies and series available on the platform, it is a perfect opportunity to flex your exploratory data analysis skills and dive into the entertainment industry.
You work for a production company that specializes in nostalgic styles. You want to do some research on movies released in the 1990's. You'll delve into Netflix data and perform exploratory data analysis to better understand this awesome movie decade!
You have been supplied with the dataset netflix_data.csv, along with the following table detailing the column names and descriptions. Feel free to experiment further after submitting!
The data
netflix_data.csv
| Column | Description |
|---|---|
show_id | The ID of the show |
type | Type of show |
title | Title of the show |
director | Director of the show |
cast | Cast of the show |
country | Country of origin |
date_added | Date added to Netflix |
release_year | Year of Netflix release |
duration | Duration of the show in minutes |
description | Description of the show |
genre | Show genre |
# Importing pandas and matplotlib
import pandas as pd
import matplotlib.pyplot as plt
# Read in the Netflix CSV as a DataFrame
netflix_df = pd.read_csv("netflix_data.csv")A. QUICK VIEW ON NETFLIX
# having a quick view the dataset from first 03 rows
netflix_df.head(3)# having a quick view the dataset from last 03 rows
netflix_df.tail(3)netflix_movies_1990s=netflix_df[(netflix_df['release_year']>=1990) & (netflix_df['release_year']<2000)]# Basic statistical analysis on the dataset
netflix_df.describe()# checking for the dimension of the dataset
netflix_df.shapeB. DATA PREPARATION
# checking the data types
netflix_df.dtypes# checking for the features infomation
netflix_df.info()# Remove any leading or trailing spaces at the columns names for easy access late
netflix_df.columns = netflix_df.columns.str.strip()# checking for any duplicate
netflix_df.duplicated().any()# Checking for null values
netflix_df.isna().any()